Datasets:

summerMC
/

LongBook-math-1M

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: string
namespace: string
text: string
metadata: struct<domain: string, difficulty: string, lang: string, kind: string, index: int64>
  child 0, domain: string
  child 1, difficulty: string
  child 2, lang: string
  child 3, kind: string
  child 4, index: int64
shards: int64
count: int64
format: string
total_chars_approx: int64
start: int64
domains: list<item: string>
  child 0, item: string
seed: int64
to
{'count': Value('int64'), 'start': Value('int64'), 'shards': Value('int64'), 'seed': Value('int64'), 'total_chars_approx': Value('int64'), 'domains': List(Value('string')), 'format': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: string
              namespace: string
              text: string
              metadata: struct<domain: string, difficulty: string, lang: string, kind: string, index: int64>
                child 0, domain: string
                child 1, difficulty: string
                child 2, lang: string
                child 3, kind: string
                child 4, index: int64
              shards: int64
              count: int64
              format: string
              total_chars_approx: int64
              start: int64
              domains: list<item: string>
                child 0, item: string
              seed: int64
              to
              {'count': Value('int64'), 'start': Value('int64'), 'shards': Value('int64'), 'seed': Value('int64'), 'total_chars_approx': Value('int64'), 'domains': List(Value('string')), 'format': Value('string')}
              because column names don't match

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LongBook Math 1M (Japanese synthetic mathematics dataset)

1,000,000 deterministic synthetic Japanese mathematics documents for retrieval evaluation and generic-model RAG, built for LongBook.

Format: JSONL, one document per line: {id, namespace, text, metadata{domain, difficulty, lang, kind, index}}
id = math-{domain}-{index:07d}, unique and sortable.
text structure (Japanese): 【分野】/【問題 id】/【解法】/【答え】/【キーワード】/【確認】
Answers are computed in Python by the generator, not hallucinated.
8 domains × 3 difficulties: arithmetic / algebra / calculus / linear_algebra / probability / geometry / number_theory / logic_sets
Generator: dataset/build_math_dataset.py (--seed 42), FTS5 ingest via dataset/bulk_ingest_math_dataset.py.
Reading guide for sub-agents: dataset/MATH_SUBAGENT.md (model-agnostic, default Qwen/Qwen3.5-9B).

Usage (datasets)

from datasets import load_dataset
ds = load_dataset("summerMC/LongBook-math-1M", split="train", data_files="math-*.jsonl")
print(ds[0])

Usage (LongBook retrieval)

python3 dataset/ingest_math_dataset.py --input <downloaded dir> --namespace math --db ./data/longbook.sqlite3
curl http://127.0.0.1:30000/v1/longbook/search \
  -H 'Content-Type: application/json' \
  -d '{"query":"二次方程式 因数分解","namespace":"math","top_k":5}'

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Total file size:

628 MB